Systems are known for obtaining tire tread surface data that provides a map of a tread surface of a tire. For instance, laser mapping systems have been used to obtain point by point data measurements of a surface of a tire. Such laser mapping systems typically include a laser probe used to measure the distance from the probe to the tire tread surface for each point along the surface of the tire. The output of these laser mapping systems provide a tread surface map for a tire. The tread surface map includes a set of data points providing a measure of tread height for a plurality of points about the surface of the tire. The tread surface map can be analyzed to assess parameters of the tire tread surface. For instance, a tread surface map can be analyzed to assess wear characteristics of the tire tread surface, such as irregular wear characteristics of the tire tread.
Known techniques for analyzing a tread surface map include modeling the tread surface using mathematical curves, such as polynomial functions. For example, U.S. Pat. No. 5,249,460 is directed to a method and apparatus for measuring irregular tread wear. In this example, data obtained from a laser scanner is analyzed and compared to a reference curve by a curve-fitting process. The deviation between the actual data and the reference curve can be used to establish the degree of irregular wear of the tire.
Using curve fitting techniques, such as polynomial curve fitting techniques, in analysis of tire tread surface data suffers several drawbacks. For example, the order of the polynomial or mathematical function must be adapted to the particular tire type, such as a truck tire versus a car tire. In many cases, the mathematical functions used to model the tire tread surface are difficult to fit with the tread surface data, leading to inaccuracies. Accuracy of the mathematical model can be increased by, for instance, increasing the degrees of freedom of the polynomial function. This, however, results in increased complexity and can lead to instability risks in fitting the mathematical function. In addition, the use of mathematical functions to model the tread surface data often do not account for discontinuities in the data or asymmetries between the left and right sides of the tire.
In typical techniques for analyzing tread surface data, such as tread surface maps, the reference for comparing the tread heights is the average tread height for the tire. This makes quantification of tread height cumbersome because the tread height values can be centered on each side of the reference with positive and negative values. In addition, the reference is not associated with the top surface of the tire as is with a manual tread gauge. Moreover, long wave deformation of the tire resulting from, for instance, false round or other uniformity parameter for the tire, can affect the reference for the tread height analysis.
Thus, a need exists for an improved system and method of analyzing tire tread surface data to assess parameters of a tread of a tire, such as irregular wear characteristics of a tread of tire. An automated system and method that more closely approximates physical observation of tread characteristics would be particularly useful.